A cloud administrator identifies performance issues: 10 VMs in pool, 15% of new service requests failing. What is the BEST approach to resolve this?

A cloud administrator identifies performance issues: 10 VMs in pool, 15% of new service requests failing. What is the BEST approach to resolve this?

• A. Check compute, storage, and networking utilization in the dashboard and increase capacity by adding more resources.
• B. Check current licensed capacity and purchase additional licenses to add more users.
• C. Check the DHCP scope and increase the number of available IP addresses by extending the pool.
• D. Check the rate-of-load increase to determine if the cloud capacity boundary has been exceeded and enable bursting to the public cloud.

Answer: (A)

The main idea here is diagnosing performance problems by inspecting current resource utilization and then scaling resources to remove bottlenecks. With 10 virtual machines and 15% of new service requests failing, the most likely issue is resource saturation in compute, storage, or networking. Starting by checking the dashboard for how these resources are being used lets you identify where the bottleneck is—CPU, memory, IOPS, bandwidth, etc.—and then you can address it by adding capacity or resizing the environment. This direct, data-driven approach targets the actual constraint and typically resolves the failure rate more reliably than changing licenses, DHCP scopes, or jumping straight to bursting without confirming where the pressure lies. Licensing and IP pool size are unrelated to the immediate performance symptoms, and bursting to the public cloud is a valid strategy only after verifying that on-prem capacity is truly exceeded and after evaluating cost and latency implications.

The main idea here is diagnosing performance problems by inspecting current resource utilization and then scaling resources to remove bottlenecks. With 10 virtual machines and 15% of new service requests failing, the most likely issue is resource saturation in compute, storage, or networking. Starting by checking the dashboard for how these resources are being used lets you identify where the bottleneck is—CPU, memory, IOPS, bandwidth, etc.—and then you can address it by adding capacity or resizing the environment. This direct, data-driven approach targets the actual constraint and typically resolves the failure rate more reliably than changing licenses, DHCP scopes, or jumping straight to bursting without confirming where the pressure lies. Licensing and IP pool size are unrelated to the immediate performance symptoms, and bursting to the public cloud is a valid strategy only after verifying that on-prem capacity is truly exceeded and after evaluating cost and latency implications.